Group Sequential Design for Randomized Phase III Trials under the Weibull Model

References

• Anderson, T. W. (1958). An Introduction to Multivariate Statistical Analysis. New York, NY: Wiley.
   Google Scholar
• Collett, D. (2003). Modeling Survival Data in Medical Research, 2nd ed, London: Chapman and Hall.
   Google Scholar
• Cox, D. R., Oakes, D. V. (1984). Analysis of Survival Data. London: Chapman and Hall.
   Google Scholar
• Haybittle, J. L. (1971). Repeated assessment of results in clinical trials of cancer treatment. British Journal of Radiology 44:793–797.
   PubMed Web of Science ®Google Scholar
• Heo, M., Faith, M. S., Allison D. B. (1998). Power and sample size for survival analysis under the Weibull distribution when the whole lifespan is of interest. Mechanisms of Ageing and Development 102:45–53.
   PubMed Web of Science ®Google Scholar
• Jennison, C., Turnbull, B. W. (2000). Group Sequential Methods with Applications to Clinical Trials. New York, NY: Chapman and Hall.
   Google Scholar
• Jiang, Z., Wang, L., Li, C., Xia, J., Jia, H. (2012). A practical simulation method to calculate sample size of group sequential trials for time-to-event under exponential and Weibull distribution. PLOS ONE 7:1–12.
   Google Scholar
• Lan, K. K. G., DeMets, D. L. (1983). Discrete sequential boundaries for clinical trials. Biometrika 70:659–663.
   Web of Science ®Google Scholar
• Lachin, J. M., Foulkes, M. A. (1986). Evaluation of sample size and power for analyses of survival with allowance for nonuniform patient entry, losses to follow-up, noncompliance, and stratification. Biometrics 42, 507–519.
   PubMed Web of Science ®Google Scholar
• Lu, Q., Tse, S. K., Chow, S. C., Lin, M. (2012). Analysis of time-to-event data nonuniform patient entry and loss to follow-up under a two-stage seamless adaptive design with Weibull distribution. Journal of Biopharmaceutical Statistics 22:773–784.
   PubMed Web of Science ®Google Scholar
• Pocock, S. J. (1977). Group sequential methods in the design and analysis of clinical trials. Biometrika 64:191–199.
   Web of Science ®Google Scholar
• Schoenfeld, D. A. (1983). Sample-size formula for the proportional-hazards regression model. Biometrics 39:499–503.
   PubMed Web of Science ®Google Scholar
• Schoenfeld, D. A., Ritcher, J. R. (1982). Nomograms for calculating the number of patients needed for a clinical trial with survival as an endpoint. Biometrics 38:163–170.
   PubMed Web of Science ®Google Scholar
• Sellke, T., Siegmund, D. (1983). Sequential analysis of the proportional hazards model. Biometrika 79:315–326.
   Google Scholar
• Slud, E. V. (1984). Sequential linear rank tests for two-sample censored survival data. Annals of Statistics, 12:551–571.
   Web of Science ®Google Scholar
• Tsiatis, A. A. (1982). Repeated significance testing for a general class of statistics used in censored survival analysis. Journal of the American Statistical Association, 77:855–861.
   Web of Science ®Google Scholar
• Tsiatis, A. A., Boucher, H., Kim, K. (1995). Sequential methods for parametric survival models. Biometrika 70:165–173.
   Google Scholar
• O’Brien, P. C., Fleming, T. R. (1979). A multiple testing procedure for clinical trials. Biometrics 35:549–556.
   PubMed Web of Science ®Google Scholar
• Whitehead, J., Stratton, I. (1983). Group sequential clinical trial with triangular continuation regions. Biometrics 39:227–236.
   PubMed Web of Science ®Google Scholar
• Wu, J. (2015). Power and sample size for randomized phase III survival trials under the Weibull model. Journal of Biopharmaceutical Statistics 25:16–28.
   PubMed Web of Science ®Google Scholar
• Xiong, X. (1995). A class of sequential conditional probability ratio tests. Journal of American Statistical Association 15:1463–1473.
   Google Scholar
• Xiong, X. (2014). A precise approach for sequential test design on comparing survival distributions by log-rank test. Unpublished Manuscript.
   Google Scholar
• Xiong, X., Tan, M., Boyett, J. (2003). Sequential conditional probability ratio tests for normalized test statistic on information time. Biometrics 59:624–631.
   PubMed Web of Science ®Google Scholar
• Xiong, X., Tan, M., Kunter, M.H. (2002). Computation methods for evaluating sequential tests and post-estimations via sufficiency principle. Statistica Sinica 12:1027–1041.
   Web of Science ®Google Scholar